Abstract
Regulatory myeloid immune cells, such as myeloid-derived suppressor cells (MDSCs), populate inflamed or cancerous tissue and block immune cell effector functions. The lack of mechanistic insight into MDSC suppressive activity and a marker for their identification has hampered attempts to overcome T cell inhibition and unleash anti-cancer immunity. Here, we report that human MDSCs were characterized by strongly reduced metabolism and conferred this compromised metabolic state to CD8+ T cells, thereby paralyzing their effector functions. We identified accumulation of the dicarbonyl radical methylglyoxal, generated by semicarbazide-sensitive amine oxidase, to cause the metabolic phenotype of MDSCs and MDSC-mediated paralysis of CD8+ T cells. In a murine cancer model, neutralization of dicarbonyl activity overcame MDSC-mediated T cell suppression and, together with checkpoint inhibition, improved the efficacy of cancer immune therapy. Our results identify the dicarbonyl methylglyoxal as a marker metabolite for MDSCs that mediates T cell paralysis and can serve as a target to improve cancer immune therapy.
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Data availability
The microarray data generated from human MDSCs compared with monocytes have been deposited in the Gene Expression Omnibus with accession code GSE131679. Source data for Figs. 1, 2 and 4–7 and Extended Data Figs. 2–5 and 8–10 are presented with the paper. The data that support the findings of this study are available from the corresponding authors upon request.
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Acknowledgements
We thank J. Schulze, M. Beyer and S. Schmitt (Life and Medical Science Institute, University of Bonn, Germany) for isolating RNA and carrying out Illumina whole-genome arrays; R. Weisskirchen (Institute of Molecular Pathobiochemistry, Experimental Gene Therapy and Clinical Chemistry, RWTH University Hospital Aachen, Germany) and J. Trebicka (Department of Internal Medicine I, University Clinic Bonn, Germany) for providing LX2 cells; R. Berger (Institute of Molecular Immunology and Experimental Oncology, Technische Universität München, Munich, Germany) for performing the seahorse experiments; and C. Llanto, S. Michailidou and S. Hegenbarth for technical support. P.A.K. and M. Heikenwälder were supported by the German Research Council (SFB TRR179) and German Center for Infection Research, Munich site. B.H. was supported by German Cancer Aid. T.K. was supported by the German Research Council (SFB1054, TR128, TR274 and SyNergy (EXC 2145; ID 390857198)) and the ERC (CoG 647215).
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T. Baumann, A.D., C.S., S.S., M. Hiltensperger, K.L., V.L., U.A., B.L.-D., J.S., L.S., N.K., T. Bauer, M.L., K.E., S.E., J.E.H., M.A., M.S. and A.H. performed the experiments and analyzed the data. S.D., J.S. and U.A. performed the bioinformatics analyses. N.H., D.H., B.S., D.S., F.A., T.W., C.F., M.S., T.M., H.Z., M. Heikenwälder, T.K., C.F., C.D. and T.H. contributed specific technologies and reagents. B.S., D.S., T.M., H.Z., M. Heikenwälder, T.K., C.D., T.H., P.J.M., P.A.K. and B.H. designed the experiments. P.J.M., P.A.K. and B.H. wrote the manuscript. All authors read and approved the manuscript.
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Extended data
Extended Data Fig. 1 Differentially expressed genes in human MDSCs compared to monocytes.
a, heatmap of differentially expressed genes in stromal cell-induced human MDSCs compared to monocytes. b, no difference in expression of genes coding for surface molecules between MDSCs and monocytes (n = 3).
Extended Data Fig. 2 Mechanistic characterization of stromal-cell induced MDSC-mediated suppression of T cell proliferation.
a-i, characterization of stromal cell-induced, human MDSCs and monocytes from the same donor. a, arginase activity measured by urea production (106 cells; n = 6 biological independent samples). b, nitric oxide-production (106 cells; n = 5 biological independent samples). c, ROS production measured by 5 µM 2,7-Dichlorodihydrofluorescein diacetate (H2DCFDA). d, CD274 (PD-L1) expression (n = 6). e, IL-10 concentration in cell culture supernatant (106 cells/ml; n = 5 biological independent samples). f and g, mRNA expression levels of TGF-beta (n = 5 biological independent samples) and Indolamine-2,3-Dioxygenase-I (IDO-I; n = 5 biological independent samples). h-i, proliferation of anti-CD3/CD28 activated CD8 T cells after co-culture with monocytes or MDSCs in presence of inhibitors: L-NOHA, arginase-I inhibitor (10 µM); L-NMMA, NO-synthase inhibitor (10 µM); MnTBAP, superoxide dismutase mimetic and peroxynitrite scavenger (40 µM); 1-MT, IDO-inhibitor (20 µM) or blocking antibodies against TGF-beta, IL-10 or PD-1 (40 µg/ml each) or transwell-insert (0.4 µm) (triplicates; n = 3). h, (n = 8 biological independent samples). j, inhibition of T cell proliferation by tumor-derived MDSCs (CD14+HLADR-/low cells; n = 3 biological independent replicates; proliferation index is plotted). ns = not significant; *p < 0.05; **p < 0.01; ***p < 0.001; ****p < 0.0001; two-way unpaired t-test.
Extended Data Fig. 3 Contact with MDSCs impairs T cell receptor cell signaling.
a-d, human CD8 T cells were activated with anti-CD3/CD28 in co-culture with MDSCs or monocytes (ratio 1:1) for 30 minutes followed by separation of CD8 T cells by FACSorting. a, pan-kinase activity in activated T cells after contact with MDSCs for 30 minutes (n = 3 biological independent samples). b, immunoblot of T cell kinase phosphorylation at indicated time points after anti-CD3/CD28 activation (n = 3 biological independent experiments). c, purity ≥ 99 % of FACSorted CD8 T cells (n = 3 biological independent experiments). d, time kinetics of T cell kinase phosphorylation detected by intracellular staining with phosphorylation-specific antibodies by flow cytometry (n = 3 biological independent samples). ns = not significant; *p < 0.05; **p < 0.01; ***p < 0.001; two-way unpaired t-test.
Extended Data Fig. 4 CD8 T cells show metabolic phenocopies of monocytes and MDSCs after co-culture.
a-f, analysis of anti-CD3/CD28 activated human CD8 T cells after coculture with MDSCs or monocytes (ratio 1:1) for 30 minutes. a, cell surface Glut-1 expression levels (n = 3 biological independent samples). b, glucose (2-NBDG) uptake (n = 3 biological independent samples). c, hexokinase activity from FACSorted CD8 T cells (triplicates; n = 3). d, glycolytic rates in FACSorted CD8 T cells by extracellular flux analysis (n = 3 biological independent samples). e, oxygen consumption rates (OCR) of FACSorted CD8 T cells (n = 3 biological independent samples). f, ATP content of CD8 T cells after FACSorting (n = 3 biological independent samples;). ns = not significant; *p < 0.05; **p < 0.01; ***p < 0.001; two-way unpaired t-test plotted as SEM.
Extended Data Fig. 5 MDSCs suppress T cell effector functions.
CD8 T cell subpopulations (naïve, effector, central memory, effector memory; from left to right) were isolated by FACS-Sorting and activated with anti-CD3/CD28 in co-culture with MDSCs or monocytes or left alone as control. a and b, intracellular staining for IFNγ, TNF and granzyme B (n = 3 independent biological experiments). c and d, quantification from (a,b). e, Granzyme B release from FACSorted CD8 T cell populations stimulated with CEF (105 T cells/ well; 2 µg/ml CEF) quantified by ELISPOT (n = 3 independent biological experiments). f and g, proliferation of FACS-Sorted CD8 T cell subpopulations measured by CFSE-dilution and quantification (n = 3 biological independent samples). Two-way unpaired t-test plotted as SEM.
Extended Data Fig. 6 Transfer of cytosolic constituents from MDSCs to CD4 T cells and NK cells.
a, transfer of cytosolic constituents from MDSCs into NKT cells and CD4 T cells (n = 3). b, gating strategy used in c and d. adoptive transfer of CD45.1+CD8 T cells (106) into CD45.2+ LysM-Cre/Rosa-mito-GFP mice tumor bearing mice (B16 melanoma cells), and flow cytometric analysis for GFP fluorescence in transferred CD45.1+CD8+ cells isolated from tumor tissue and spleen directly ex vivo at 24 hours after transfer (n = 4). d, proliferation of isolated and activated CD8 T cells from tumor tissue and spleen was analyzed on day 3 using flow cytometry (c, d, representative plots of n = 4 biological independent samples).
Extended Data Fig. 7 Detection of methylglyoxal and its generation and neutralization.
a, derivatization of carbonyl compounds with 3-Nitrophenylhydrazine (3-NPH) for detection by mass spectrometry. b, Methylglyoxal content measurement in different immune cells from the peripheral blood of HCC patients (n = 3). c, Chemical formulas for molecules with guanidine-groups that are targets of methylglyoxal (red boxes).
Extended Data Fig. 8 Guanidine-treatment of MDSCs abrogates their suppressive activity on CD8 T cell effector functions.
a-c and e,f, human CD8 T cells were cultures in the presence of MDSCs that were partially pretreated with indicated compounds. a, T cells were stimulated alone, treated with DMBG, in the presence of MDSCs (pretreated with DMBG, methylguanidine, aminoguanidine or rodenidine (200 µM each). Proliferation (a) or cytotoxic activity (b) was measured by the dilution of CFSE (n = 3) or by ELISpot (n = 3 biological independent samples). d, Suppressive activity of CD11b+Ly6C+ or CD11b+Ly6G+ cells from the central nerves system during the recovery phase of experimental autoimmune encephalomyelitis (EAE; day 22 after immunization partially pretreated with DMBG (n = 3). e activated CD8 T cells were cocultured with CD4+CD25+CD127- regulatory T cells. Were Indicated, DMBG (200 µM) were added and proliferation was measured on day 3 (n = 3 biological independent samples). f, CD15+ cells were isolated from blood from the same patient were isolated an cocultured with CFSE labeled, activated CD8 T cells. Proliferation was measured by the dilution of CFSE (n = 2 biological independent samples). g, h, T cells were cocultivated with MDSCs for 30 min and reisolated. The glucose uptake capacity (2-NBDG) was measured at 30 min intervals (n = 3 biological independent samples). h, continuous glucose uptake measurement after addition of DMBG (n = 3), live-dead discrimination of CD8 T cells cultured alone, with monocytes or with MDSCs (n = 5 biological independent samples). j, cell count of CD8 T cells cultured alone, with monocytes or with MDSCs (n = 3 biological independent samples). *p < 0.05; **p < 0.01; ***p < 0.001; two-way unpaired t-test.
Extended Data Fig. 9 Monocytic cells affect the amino acid composition of CD8 T cells.
Free amino acids and advanced glycation products were measured using SIDA-UHPLC-MS/MSMRM in T cells after co-culture with MDSCs or monocytes. (n = 4 biological independent samples (3 biological samples for T cells without stimulation)). ns = not significant; two-way unpaired t-test; indicating no significant differences between any groups.
Extended Data Fig. 10 DMBG restores effector function of vaccination-induced CD8 T cells in cancer tissue.
At d10 after s.c. B16-OVA cancer cell inoculation, mice received ovalbumin adjuvanted with CpG/alphaGalCer, anti-PD-1 (200 µg/every 3. Day) and/or DMBG in drinking water (40 mM), and analyses were performed at d17 (5 animals per group; n = 3). a, Kaplan-Meier survival curves of tumor bearing mice (n = 5). b, the expression of ovalbumin was tested in B16-melanoma in cell culture (1), ex vivo after vaccination on day 17 (2) and on day 34 after combined therapy using anti-PD-1 and DMBG alone (3,4) or in combination with vaccination (5,6) (n = 3 independen biological samples). c - e, MBo-fluorescence and glucose uptake of CD11b+ cells from spleen. f, g CD8 T cell proliferation (CFSE-dilution) in co-culture with CD11b+Ly6C+ cells or CD11b+Ly6G+ (FACSorted) from cancer tissue or spleen (numbers denote division indices). h, i, MBo-fluorescence and glucose uptake of CD8+ T cells from the spleen (a, c – e: n = 6 biological independent samples; g – i: n = 5 biological identical samples). ns = not significant; indicating no significant differences between any groups.; *p < 0.05; **p < 0.01; ***p < 0.001; two-way unpaired t-test or 2-sided Mantel-Cox test (survival curve).
Supplementary information
Supplementary Tables
Supplementary Table 1: Patient classification. Supplementary Table 2: All DEGs in MDSCs compared with monocytes. Supplementary Table 3: Immune regulatory genes in MDSCs compared with monocytes. Supplementary Table 4: Significantly DEGs in MDSCs compared with monocytes. Supplementary Table 5: All differentially expressed surface markers in MDSCs compared with monocytes (Cell Surface Protein Atlas dataset)66. Supplementary Table 6: All differentially expressed glycolytic enzyme genes in MDSCs compared with monocytes. Supplementary Table 7: Metabolites in MDSCs compared with monocytes. Supplementary Table 8: MRM transitions and optimized MS/MS parameters for AGP analysis. Supplementary Table 9: MRM transitions and optimized MS/MS parameters for amino acid analysis.
Supplementary Video 1
Three-dimensional reconstruction from high-resolution confocal imaging of the interaction between a MitoTracker Green–labeled MDSC (right cell in image) interacting with a T cell (left cell in image), illustrating transfer of the MitoTracker Green label or labeled cytosolic constituents from the MDSC to the T cell and the formation of a physical connection between the two cells that might allow for transfer of cytosolic constituents.
Supplementary Video 2
Time-lapse confocal microscopy of the interaction between anti-CD8-eF670-labeled T cells and MitoTracker Green–labeled MDSCs, showing that eF670-positive T cells acquire MitoTracker Green fluorescence only when located in the direct vicinity of MDSCs, to allow for physical contact between the two cell populations.
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Baumann, T., Dunkel, A., Schmid, C. et al. Regulatory myeloid cells paralyze T cells through cell–cell transfer of the metabolite methylglyoxal. Nat Immunol 21, 555–566 (2020). https://doi.org/10.1038/s41590-020-0666-9
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DOI: https://doi.org/10.1038/s41590-020-0666-9
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